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rahulkr

Enhanced ADB MCP Server

by rahulkr
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Python
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get_gpu_info

Retrieve GPU rendering data from Android devices to identify performance bottlenecks and debug graphics issues during development.

Instructions

Get GPU rendering information - useful for performance debugging

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
device_serialNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • src/adb_mcp_server/server.py:802-805 (handler)
    The get_gpu_info tool handler function. It runs 'adb shell dumpsys gfxinfo' to retrieve GPU rendering information. The @mcp.tool() decorator registers it with the MCP server.
    @mcp.tool()
def get_gpu_info(device_serial: str | None = None) -> str:
    """Get GPU rendering information - useful for performance debugging"""
    return run_adb(["shell", "dumpsys", "gfxinfo"], device_serial)

Tool Definition Quality

B3.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves information (implying read-only), but doesn't mention any side effects, permissions needed, rate limits, or what happens if the device_serial is invalid. For a diagnostic tool with zero annotation coverage, this leaves significant behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise (one sentence) and front-loaded with the core purpose. Every word earns its place, with no redundant information or unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's diagnostic nature, one parameter, and an output schema (which handles return values), the description is minimally adequate. However, with no annotations and incomplete parameter documentation, it lacks context about behavioral constraints and parameter usage, making it incomplete for optimal agent understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, so the description must compensate. It doesn't mention the device_serial parameter at all, leaving its purpose and format undocumented. However, with only one optional parameter, the baseline is higher, but the description adds no value beyond what's implied by the tool name.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('GPU rendering information'), and adds a use case ('performance debugging'). However, it doesn't explicitly differentiate from sibling tools like get_cpu_info or get_memory_info, which have similar diagnostic purposes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a general use case ('performance debugging') but offers no explicit guidance on when to use this tool versus alternatives like get_cpu_info or get_frame_stats. There's no mention of prerequisites, exclusions, or specific scenarios where this tool is preferred over others.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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